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V0305P5
Litzy619/V0305P5
V0305P5 is a machine learning model from Litzy619. Use it for the machine learning task on the model card, and read the license before you ship it in a product. The card lists the license as other.
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Public
Updated Mar 12, 2024
Parameters
6.8B
28.3 GB on disk
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.safetensors13.8 GB · 98%
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F166.7B · 99%
Base models
Model card
From the Hugging Face model README
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
V0305P5
This model is a fine-tuned version of yahma/llama-7b-hf on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0750
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.0003
- train_batch_size: 4
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 32
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine_with_restarts
- lr_scheduler_warmup_steps: 20
- num_epochs: 3
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 1.3878 | 0.09 | 10 | 0.1658 |
| 0.2801 | 0.17 | 20 | 0.1531 |
| 0.1578 | 0.26 | 30 | 0.1529 |
| 0.1521 | 0.34 | 40 | 0.1514 |
| 0.1515 | 0.43 | 50 | 0.1508 |
| 0.1567 | 0.51 | 60 | 0.1507 |
| 0.1517 | 0.6 | 70 | 0.1491 |
| 0.1531 | 0.68 | 80 | 0.1480 |
| 0.149 | 0.77 | 90 | 0.1474 |
| 0.153 | 0.85 | 100 | 0.1521 |
| 0.1511 | 0.94 | 110 | 0.1264 |
| 0.14 | 1.02 | 120 | 0.1210 |
| 0.1316 | 1.11 | 130 | 0.1209 |
| 0.1198 | 1.19 | 140 | 0.1015 |
| 0.1105 | 1.28 | 150 | 0.0888 |
| 0.1067 | 1.37 | 160 | 0.0930 |
| 0.1043 | 1.45 | 170 | 0.0852 |
| 0.0962 | 1.54 | 180 | 0.0887 |
| 0.0968 | 1.62 | 190 | 0.0805 |
| 0.0957 | 1.71 | 200 | 0.0824 |
| 0.0939 | 1.79 | 210 | 0.0819 |
| 0.0918 | 1.88 | 220 | 0.0803 |
| 0.0865 | 1.96 | 230 | 0.0818 |
| 0.0734 | 2.05 | 240 | 0.0791 |
| 0.0591 | 2.13 | 250 | 0.0743 |
| 0.0614 | 2.22 | 260 | 0.0709 |
| 0.0544 | 2.3 | 270 | 0.0836 |
| 0.0611 | 2.39 | 280 | 0.0747 |
| 0.064 | 2.47 | 290 | 0.0711 |
| 0.0582 | 2.56 | 300 | 0.0721 |
| 0.0646 | 2.65 | 310 | 0.0752 |
| 0.0551 | 2.73 | 320 | 0.0761 |
| 0.0571 | 2.82 | 330 | 0.0753 |
| 0.0562 | 2.9 | 340 | 0.0750 |
| 0.0537 | 2.99 | 350 | 0.0750 |
Framework versions
- Transformers 4.36.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.14.6
- Tokenizers 0.14.1
- License
- other
- Created
- Mar 6, 2024
- Updated
- Mar 12, 2024